How the DataKitchen DataOps Platform Delivers End-to-End Data Observability
Data errors are crippling data teams. In a recent survey, eighty percent of companies reported three or more errors per month. Thirty percent of respondents reported more than 11 errors per month. Finding and fixing errors sends data teams into a tailspin, increases data downtime, and reduces customer trust in the quality of the analytics.
Automated testing and monitoring are foundational to a successful DataOps program. By testing and monitoring every step in your end-to-end production and development pipelines, data teams can eliminate errors and dramatically increase data reliability.
Learn how DataOps enables data observability and reduces data downtime. Specifically, Chris covers:
- The duality of tests in production & development;
- How to meta-orchestrate tests across your entire analytic system;
- The types of tests you need; &
- How to get started with testing & monitoring.
About the Speaker
Chris Bergh is Co-Founder, CEO, and Head Chef of DataKitchen, a DataOps software and services startup. He has more than 30 years of research, software engineering, data analytics, and executive management experience. At various points in his career, he has been a COO, CTO, VP, and Director of Engineering. Chris is a recognized expert on DataOps. He is the co-author of the DataOps Cookbook and the DataOps Manifesto, and a speaker on DataOps at many industry conferences. You can follow Chris on Twitter @ChrisBergh or connect with him on LinkedIn.